Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add letitbk/claude-academic-setup --skill discuss-claimsgit clone --depth 1 https://github.com/letitbk/claude-academic-setupWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/letitbk/claude-academic-setup/discuss-claims)<a href="https://agentmods.dev/skills/letitbk/claude-academic-setup/discuss-claims"><img src="https://agentmods.dev/badge/skills/letitbk/claude-academic-setup/discuss-claims/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/letitbk/claude-academic-setup/discuss-claims"><img src="https://agentmods.dev/badge/skills/letitbk/claude-academic-setup/discuss-claims.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01440 |
| Opus 5 | $0.00029 | $0.00720 |
| Sonnet 5 | $0.00012 | $0.00288 |
| Haiku 4.5 | $0.00006 | $0.00144 |
Grade A, and why
discuss-claims scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discuss Claims
Post self-contained GitHub issues for internal team discussion of core empirical claims. Each issue covers one claim: motivation, methods, findings (with inline figure/table links), interpretation, implications, and limitations.
When to Use
- User wants to share analysis findings with co-authors via GitHub Issues
- User says "post issues", "create claim issues", "discuss on GitHub", "set up review"
- Analysis pipeline is complete and output files exist
When NOT to Use
- User wants a formal reviewer template with feedback/decision boxes (this skill creates discussion threads, not review forms)
- Repo is public and findings are embargoed
- Output files have not been generated yet
Workflow
Phase 0: Pre-flight
Run these checks before touching GitHub. Fix any failures before proceeding.
# 1. Issues enabled?
gh repo view OWNER/REPO --json hasIssuesEnabled
# 2. Existing [DISCUSS] issues?
gh issue list --state open | grep "\[DISCUSS\]"
# 3. Find untracked output files and auto-commit them
git ls-files --others --exclude-standard output/
# If any exist: git add output/ && git commit -m "Add output files for co-author review" && git push
CRITICAL — broken links are the #1 failure mode: GitHub blob links return 404 if the file is not committed and pushed. Always verify with git ls-files --error-unmatch <file> for at least a sample of referenced figures/tables before creating any issue.
Phase 1: Collect Project Metadata
Infer from git or ask the user:
- GitHub repo:
owner/repo(infer fromgit remote get-url origin) - Branch:
masterormain(infer fromgit symbolic-ref refs/remotes/origin/HEAD) - Output directories: where figures and tables live (default:
output/figures/,output/tables/)
Construct the base blob URL:
https://github.com/OWNER/REPO/blob/BRANCH/PATH/TO/file.png
Phase 2: Discover Output Files
Scan the output directories and build a menu for the user to pick from per claim:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 149 lines · 58 tokens per session scan A b0700ac7f7a0
discuss-claims is a skill published in the GitHub repository letitbk/claude-academic-setup (45 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 1,440 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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